To perform well in a familiar but complex task like reading, processing resources must be appropriately allocated to each of the sub-components of reading, such as recognizing words, determining the syntactic and semantic relations, inferring the referents, and organizing the information within a schema. Not all components of reading require the same allocation of resources. For a skilled reader, word recognition requires so few resources that it is automatic. By contrast, understanding the implications of a technical paragraph requires considerable attention, and may be beyond the resources of a less skilled reader. The proposed research will determine how readers in various tasks allocate processing resources to the components of reading comprehension. The experiments will measure the effects of different attention allocations by comparing the reading in normal conditions to reading performed concurrently with another task, or reading which is focused on one particular component, as in searching for a fact or proofreading. The experiments examine the comprehension processes as they occur by monitoring the readers' eye fixations on the text and using these data as indicators of the characteristics of the underlying processes. Post-reading comprehension tests assess the knowledge that was produced by the various processes. The proposed research will determine which components of reading are relatively immune to attention shifts and proceed normally regardless of competing tasks and attention-directing instructions, which ones become disengaged when processing resources are drawn away from them, and which ones compete with each other for attentional resources. The models and methodologies developed for normal reading enable us to address questions of individual differences in reading ability, reading retardation, and dyslexia. More generally, the eye-fixation methodology is providing a powerful new tool to examine how brain mechanisms operate normally or abnormally in fundamental thought processes. The medical and educational value of these analytic tools is not just a promise for the future, but is currently available for use in the service of education and mental health.